Simulating how atoms and molecules move over time is a central challenge in computational chemistry and materials science. Classical machine learning approaches to molecular dynamics (MD) encode ...
Researchers from BIFOLD and Google DeepMind have developed MD-ET, a transformer-based molecular dynamics model that omits traditional physics constraints like energy conservation and equivariance.
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